FEASIBILITY OF RAPID DIAGNOSIS OF COLORECTAL CANCER BY NEAR-INFRARED SPECTROSCOPY AND SUPPORT VECTOR MACHINE

作者：Chen Hui; Tan Chao^*; Wu Hegang; Lin Zan; Wu Tong

来源：Analytical Letters, 2014, 47(15): 2580-2593.

DOI：10.1080/00032719.2014.915410

• Colorectal cancer
• Near-infrared spectroscopy
• NIR
• Support vector machine

The feasibility of diagnosing colorectal cancers based on the combination of near-infrared (NIR) spectroscopy and supervised pattern recognition methods was investigated. A total of fifty-eight colorectal tissues were collected and prepared. The spectra were first preprocessed by standard normalize variate (SNV) and first derivatives of Savitzky-Golay polynomial filter for removing unwanted background variances. The information of CH-stretching overtones and combination regions proved to be the most valuable. Four pattern recognition methods including K-nearest neighbor classifier (KNN), perceptron, Fisher discriminant analysis (FDA), and support vector machine (SVM) were used for constructing classifiers. In terms of the total accuracy, sensitivity and specificity, the SVM classifier achieved the best performance; the sensitivity and specificity were 92.8% and 86.7%, respectively. These findings suggest that NIR spectroscopy offers the possibility of constructing a simple, feasible and sensitive method for diagnosing colorectal cancer, avoiding the need of laborious visual inspection from experts.

• 出版日期2014
• 单位四川大学; 宜宾学院